System and method for online analysis

ABSTRACT

A method is disclosed. The method includes receiving, from a user computer that is a party to a transaction, information that can be used to identify a transaction between the user computer and a resource provider computer. The method further includes determining one or more attributes. The method additionally includes presenting a first question based on the one or more attributes. The method also includes receiving a response to the first question, presenting a second question based on the received response, and receiving a response to the second question. The method further includes storing the received responses in a data storage element, wherein the data storage element is accessible by an authorizing entity computer.

CROSS-REFERENCES TO RELATED APPLICATIONS

Not applicable.

BACKGROUND

Traditional processes for dispute resolution are slow and requireinteraction between the party initiating the dispute and the partymediating the dispute. The collection of facts pertinent to a particulardispute is also difficult. For example, in the context of a disputeinvolving a user and a merchant, users are generally required to place acall to the party mediating the dispute (e.g., an issuer) and providebasic and redundant information regarding the transaction beingdisputed. Additionally, the user may be required to provide signedletters before disputes can be initiated. User dispute letters oftencontain many facts that are not relevant to resolving the dispute; orconversely, these letters may be missing requests for information neededto resolve a particular dispute. Furthermore, many issuers use their ownform letters. These letters cause difficulties for merchants byproviding inconsistent information in different formats. Acquirers andprocessors also use different proprietary letters to communicate withissuers, adding to the complexity of conventional dispute resolutionprocesses. Depending upon the type of dispute, the entire process ofgathering the needed information for the entity that will ultimatelydecide the dispute may take several minutes to hours, depending upon thecircumstances.

The tedious process of providing the information to the party mediatingthe dispute prior to any action regarding the resolution of the disputeoften results in user frustration. The user may feel that they wastedtime contacting the party mediating the dispute and providinginformation about the transaction, only to wait for an uncertain amountof time for the dispute to be resolved. Additionally, conventionaldispute resolution processes are not efficient because a live personrepresenting the party mediating the dispute is required to gather factspertaining to the dispute from the user.

Embodiments of the invention address these and other problems.

SUMMARY

A system of one or more computers can be configured to performparticular operations or actions by virtue of having software, firmware,hardware, or a combination of them installed on the system that inoperation causes or cause the system to perform the actions. One or morecomputer programs can be configured to perform particular operations oractions by virtue of including instructions that, when executed by dataprocessing apparatus, cause the apparatus to perform the actions. Onegeneral aspect includes a method for automated analysis using machinelearning, including: receiving, from a user computer that is a party toa transaction and at a server computer, information that can be used toidentify a transaction between the user computer and a resource providercomputer. The method also includes determining, by the server computerand from a database, one or more attributes associated with thetransaction and one or more attributes associated with the resourceprovider computer. The method also includes presenting, by the servercomputer, a first question pertaining to the transaction based at leastin part on the accessed one or more attributes associated with theidentified transaction and the accessed one or more attributesassociated with the resource provider computer. The method also includesreceiving, from the user computer and by the server computer, a responseto the first question. The method also includes presenting, by theserver computer, a second question pertaining to the transaction basedat least in part on the received response to the first question. Themethod also includes receiving, from the user computer and by the servercomputer, a response to the second question. The method also includesstoring, by the server computer, the received first response and thereceived second response in a data storage element, where the datastorage element is accessible by an authorizing entity computer. Otherembodiments of this aspect include corresponding computer systems,apparatus, and computer programs recorded on one or more computerstorage devices, each configured to perform the actions of the methods.

Implementations may include one or more of the following features. Themethod where the data storage element is accessible by the authorizingentity computer via an online resolution analysis system. The methodwhere the information that can be used to identify the transactionbetween the user computer and a resource provider computer is receivedvia an application associated with the resource provider computerexecuting on the user computer. The method where the one or moreattributes associated with the transaction and the one or moreattributes associated with the resource provider computer are determinedautomatically by the server computer by receiving only an identifierassociated with the user computer. The method where the first questionand the second question are part of an interview script that isautomatically created using a machine learning algorithm, the machinelearning algorithm including a neural network or a k-means algorithm.The method where the first question and the second question are part ofan interview script that is automatically created using data from aprocessing network that operates as a switch. The method furtherincluding providing, by the server computer and to the user computer,one or more options for answering the first and second questions. Themethod where the one or more options are based at least in part on theresponse to the first question, the response to the second question, theaccessed one or more attributes associated with the identifiedtransaction, or the accessed one or more attributes associated with theresource provider computer. The method where the one or more options arebased at least in part on a ruleset applied to the dispute, where theruleset is based at least in part on the accessed one or more attributesassociated with the resource provider computer. The method where thefirst question and the second question are generated by a machinelearning model. Implementations of the described techniques may includehardware, a method or process, or computer software on acomputer-accessible medium.

One general aspect includes a server computer, including: a processor;and a non-transitory computer readable medium, the non-transitorycomputer readable medium including computer executable code forexecuting a method for resolving a dispute, the method including. Theserver computer also includes receiving, from a user computer that is aparty to a transaction, information that can be used to identify atransaction between the user computer and a resource provider computer.The server computer also includes determining, from a database, one ormore attributes associated with the transaction and one or moreattributes associated with the resource provider computer. The servercomputer also includes presenting a first question pertaining to thetransaction based at least in part on the accessed one or moreattributes associated with the identified transaction and the accessedone or more attributes associated with the resource provider computer.The server computer also includes receiving, from the user computer, aresponse to the first question. The server computer also includespresenting a second question pertaining to the transaction based atleast in part on the received response to the first question. The servercomputer also includes receiving, from the user computer, a response tothe second question. The server computer also includes storing thereceived first response and the received second response in a datastorage element, where the data storage element is accessible by anauthorizing entity computer. Other embodiments of this aspect includecorresponding computer systems, apparatus, and computer programsrecorded on one or more computer storage devices, each configured toperform the actions of the methods.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a block diagram of an online resolution analysis system,according to some embodiments.

FIG. 2 shows a flowchart illustrating a process for online disputeresolution analysis, according to some embodiments.

FIG. 3 shows a server computer, according to some embodiments.

FIG. 4A shows another screenshot of a user interaction with the onlinedispute resolution system via a user interface of an applicationexecuting on the user computer 120, according to some embodiments.

FIG. 4B shows another screenshot of a user interaction with the onlinedispute resolution system via a user interface of an applicationexecuting on the user computer 120, according to some embodiments.

FIG. 5 shows a block diagram of a transaction processing system that canuse a portable device with access data according to an embodiment of theinvention.

DETAILED DESCRIPTION

Prior to discussing embodiments of the invention, descriptions of someterms may be helpful in understanding embodiments of the invention.

A “user computer” may be a computer operated by a user. Exemplary usercomputers may include mobile communication devices. A “mobilecommunication device” may be an example of a “communication device” thatcan be easily transported. A mobile communication device may also haveremote communication capabilities. Examples of remote communicationcapabilities include using a mobile phone (wireless) network, wirelessdata network (e.g. 3G, 4G or similar networks), Wi-Fi, Wi-Max, or anyother communication medium that may provide access to a network such asthe Internet or a private network. Examples of mobile communicationdevices include mobile phones (e.g. cellular phones), PDAs, tabletcomputers, net books, laptop computers, personal music players,hand-held specialized readers, etc. Further examples of mobilecommunication devices include wearable devices, such as smart watches,fitness bands, ankle bracelets, rings, earrings, etc., as well asvehicles such as automobiles with remote communication capabilities. Insome embodiments, a mobile communication device can function as apayment device (e.g., a mobile communication device can store and beable to transmit payment credentials for a transaction).

A “payment device” may include any suitable device that may be used toconduct a financial transaction, such as to provide payment credentialsto a merchant. Suitable payment devices can be hand-held and compact sothat they can fit into a user's wallet and/or pocket (e.g.,pocket-sized). Example payment devices may include smart cards, keychaindevices (such as the Speedpass™ commercially available from Exxon-MobilCorp.), etc. Other examples of payment devices include payment cards,smart media, transponders, and the like. If the payment device is in theform of a debit, credit, or smartcard, the payment device may alsooptionally have features such as magnetic stripes. Such devices canoperate in either a contact or contactless mode.

A “credential” may be any suitable information that serves as reliableevidence of worth, ownership, identity, or authority. A credential maybe a string of numbers, letters, or any other suitable characters, aswell as any object or document that can serve as confirmation.

“Payment credentials” may include any suitable information associatedwith an account (e.g. a payment account and/or payment device associatedwith the account). Such information may be directly related to theaccount or may be derived from information related to the account.Examples of account information may include a PAN (primary accountnumber or “account number”), user name, expiration date, andverification values such as CVV, dCVV, CVV2, dCVV2, and CVC3 values.

A “user” may include an individual. In some embodiments, a user may beassociated with one or more personal accounts and/or mobile devices. Theuser may be a cardholder, an account holder, or a consumer in someembodiments.

A “resource provider” may be an entity that can provide a resource suchas goods, services, information, and/or locations. Examples of resourceproviders includes merchants, data providers, transit agencies,governmental entities, venue and dwelling operators, etc.

A “merchant” may typically be an entity that engages in transactions andcan sell goods or services, or provide access to goods or services.

An “acquirer” may typically be a business entity (e.g., a commercialbank) that has a business relationship with a particular merchant orother entity. Some entities can perform both issuer and acquirerfunctions. Some embodiments may encompass such single entityissuer-acquirers. An acquirer may operate an acquirer computer, whichcan also be generically referred to as a “transport computer”.

An “authorizing entity” may be an entity that authorizes a request.Examples of an authorizing entity may be an issuer, a governmentalagency, a document repository, an access administrator, etc. Anauthorizing entity may operate an authorization computer.

An “issuer” may typically refer to a business entity (e.g., a bank) thatmaintains an account for a user. An issuer may also issue paymentcredentials stored on a portable device, such as a cellular telephone,smart card, tablet, or laptop to the consumer.

A “resolution analysis system” may be a system that is involved in theprocess of resolving disputes between parties. A dispute may be asituation in which a user questions the validity of a transaction thatwas registered to his/her account. Users may dispute charges for avariety of reasons, including unauthorized charges, excessive charges,failure by the merchant to deliver merchandise, defective merchandise,dissatisfaction with the product(s) or service(s) received, or billingerrors. The resolution analysis system may facilitate the resolution ofsuch disputes by gathering information associated with the dispute andresolving the dispute in favor of one party or another. A resolutionanalysis system may be a dispute resolution system.

An “access device” may be any suitable device that provides access to aremote system. An access device may also be used for communicating witha merchant computer, a transaction processing computer, anauthentication computer, or any other suitable system. An access devicemay generally be located in any suitable location, such as at thelocation of a merchant. An access device may be in any suitable form.Some examples of access devices include POS or point of sale devices(e.g., POS terminals), cellular phones, PDAs, personal computers (PCs),tablet PCs, hand-held specialized readers, set-top boxes, electroniccash registers (ECRs), automated teller machines (ATMs), virtual cashregisters (VCRs), kiosks, security systems, access systems, and thelike. An access device may use any suitable contact or contactless modeof operation to send or receive data from, or associated with, a mobilecommunication or payment device. In some embodiments, where an accessdevice may comprise a POS terminal, any suitable POS terminal may beused and may include a reader, a processor, and a computer-readablemedium. A reader may include any suitable contact or contactless mode ofoperation. For example, exemplary card readers can include radiofrequency (RF) antennas, optical scanners, bar code readers, or magneticstripe readers to interact with a payment device and/or mobile device.In some embodiments, a cellular phone, tablet, or other dedicatedwireless device used as a POS terminal may be referred to as a mobilepoint of sale or an “mPOS” terminal.

An “authorization request message” may be an electronic message thatrequests authorization for a transaction. In some embodiments, it issent to a transaction processing computer and/or an issuer of a paymentcard to request authorization for a transaction. An authorizationrequest message according to some embodiments may comply with ISO 8583,which is a standard for systems that exchange electronic transactioninformation associated with a payment made by a user using a paymentdevice or payment account. The authorization request message may includean issuer account identifier that may be associated with a paymentdevice or payment account. An authorization request message may alsocomprise additional data elements corresponding to “identificationinformation” including, by way of example only: a service code, a CVV(card verification value), a dCW (dynamic card verification value), aPAN (primary account number or “account number”), a payment token, auser name, an expiration date, etc. An authorization request message mayalso comprise “transaction information,” such as any informationassociated with a current transaction, such as the transaction amount,merchant identifier, merchant location, acquirer bank identificationnumber (BIN), card acceptor ID, information identifying items beingpurchased, etc., as well as any other information that may be utilizedin determining whether to identify and/or authorize a transaction.

An “authorization response message” may be a message that responds to anauthorization request. In some cases, it may be an electronic messagereply to an authorization request message generated by an issuingfinancial institution or a transaction processing computer. Theauthorization response message may include, by way of example only, oneor more of the following status indicators: Approval—transaction wasapproved; Decline—transaction was not approved; or Call Center—responsepending more information, merchant must call the toll-free authorizationphone number. The authorization response message may also include anauthorization code, which may be a code that a credit card issuing bankreturns in response to an authorization request message in an electronicmessage (either directly or through the transaction processing computer)to the merchant's access device (e.g. POS equipment) that indicatesapproval of the transaction. The code may serve as proof ofauthorization.

A “server computer” may include a powerful computer or cluster ofcomputers that services the requests of one or more client computers.For example, the server computer can be a large mainframe, aminicomputer cluster, or a group of servers functioning as a unit. Inone example, the server computer may be a database server coupled to aWeb server. The server computer may comprise one or more computationalapparatuses and may use any of a variety of computing structures,arrangements, and compilations for servicing the requests from one ormore client computers.

A “memory” may be any suitable device or devices that can storeelectronic data. A suitable memory may comprise a non-transitorycomputer readable medium that stores instructions that can be executedby a processor to implement a desired method. Examples of memories maycomprise one or more memory chips, disk drives, etc. Such memories mayoperate using any suitable electrical, optical, and/or magnetic mode ofoperation.

A “processor” may refer to any suitable data computation device ordevices. A processor may comprise one or more microprocessors workingtogether to accomplish a desired function. The processor may include CPUcomprises at least one high-speed data processor adequate to executeprogram components for executing user and/or system-generated requests.The CPU may be a microprocessor such as AMD's Athlon, Duron and/orOpteron; IBM and/or Motorola's PowerPC; IBM's and Sony's Cell processor;Intel's Celeron, Itanium, Pentium, Xeon, and/or XScale; and/or the likeprocessor(s).

FIG. 1 shows a block diagram of an online resolution analysis system100, according to some embodiments. The online resolution analysissystem 100 may include an authorizing entity computer 110, user computer120, resource provider computer 130, and server computer 140. Each ofthe authorizing entity computer 110, user computer 120, resourceprovider computer 130, and server computer 140 may be communicativelycoupled to each other via an interconnected network, such as at theInternet.

The online resolution analysis system 100 may gather informationpertaining a dispute by using a series of prompts to identify theinformation necessary to resolve a dispute (e.g., a disputedtransaction). Traditionally, this information may be collected from auser of the user computer 120 by an agent or a caseworker associatedwith the authorizing entity computer 110. The agent or caseworker mayask questions to the user, obtain the necessary information, open aticket, and perform further investigation pertaining to the dispute. Theonline resolution analysis system 100 is more efficient thanconventional dispute resolution systems, since it can automaticallygathering this information, without the need for an agent or caseworker.The online resolution analysis system 100 can do this by producing aseries of unique prompts to be presented to the user via the usercomputer 120. Answers provided by the user of the user computer 120 tothe series of prompts are used to obtaining the information needed toresolve the dispute. The series of prompts may be generated via amachine learning model where the prompts may be generated in real-timebased on the user's responses to prior prompts and based on additionalknowledge of the transaction. Suitable machine learning models may bebased on algorithms including: neural networks, decision trees, supportvector methods, and K-means algorithms. The online resolution analysissystem 100 may also provide for the automatic gathering of factsassociated with a disputed transaction which may also be used in theresolution process. Other details regarding the online resolutionanalysis system 100 and the functions that it can perform are providedbelow.

At step s1, the user computer 120 initiates a transaction with theresource provider computer 130. The resource provider computer 130 maybe associated with a merchant that provides goods or services forpurchase. The transaction initiated by the user computer 120 may be forone or more goods or services available from the merchant that the userof the user computer 120 wishes to purchase. The resource providercomputer 130 may include or operate an access device and the usercomputer 120 may interface with the resource provider computer 130 tobegin the transaction. Upon the transaction being initiated, thetransaction may proceed and complete according to any known paymenttransaction protocols. That is, upon the transaction being approved, anaccount associated with the user of the user computer 120 may be debitedin the amount of the total goods or services purchased from themerchant. Further details regarding a typical payment transaction aredescribed below, with reference to FIG. 5.

In some examples, the user computer 120 may be a smartphone device,tablet, wearable device, etc. In some examples, the user computer 120can be a physical payment card that used for interacting with theresource provider computer 130. Accordingly, the online resolutionanalysis system 100 may support both card present and card-not-presenttransactions.

At step s2, after the user computer 120 initiates the transaction withthe resource provider computer 130, the merchant associated with theresource provider computer 130 may dispatch the goods to the user of theuser computer 120. For example, if the transaction was an in-persontransaction at a merchant location, the user may take the goods withhim/her as he/she exits the merchant location upon the transaction beingcompleted. In another example, if the transaction was an onlinetransaction, the goods may be shipped to the user of the user computer120.

At step s3, after the merchant associated with the resource providercomputer 130 dispatches the goods to the user of the user computer 120,the user of the user of the user computer 120 may initiate a disputeprocess against a merchant associated with the resource providercomputer 130, with the authorizing entity computer 110. The user mayinitiate a dispute process for the transaction completed in step s2 forany number of reasons, including unauthorized charges, excessivecharges, failure by the merchant to deliver merchandise, defectivemerchandise, dissatisfaction with the product(s) or service(s) received,or billing errors. Additionally, the user may initiate the disputeprocess if attempts to come to a resolution directly with the merchanthave been unsuccessful. For example, if the user received a defectiveproduct from the merchant, and the merchant refuses to issue a refund tothe user for the defective product, the user may initiate the disputeprocess.

At step s4, after the user of the user of the user computer 120initiates the dispute process with the authorizing entity computer 110,the authorizing entity computer 110 may notify the server computer 140of the initiated dispute, and the server computer 140 may performreal-time research pertaining to the disputed transaction. The servercomputer may be an online resolution analysis server computer. In someembodiments, the user, using the user computer 120, may only need tosupply basic information such as the account number of the paymentaccount used to conduct the transaction, the merchant name, and/or thedate (and/or time) of the transaction. In some cases, even the credit ordebit card account number need not be provided, as the device identifier(e.g., a phone number) of the user computer 120 may be linked to theuser's debit or credit card number, and the server computer 110 mayautomatically determine the credit or debit card account used by theuser computer 120. By only requiring the user to provide basicinformation related to the transaction, the user experience is improvedand there may be less friction when a user attempts to initiate adispute.

The research performed by the server computer may include gatheringinformation or attributes associated with the disputed transaction andinformation or attributes associated with the merchant. For example, theserver computer 140 may determine the good/service for which thetransaction was completed, the amount of the transaction, the time ofthe transaction, the date of the transaction, which type of device thetransaction was initiated from, a website associated with thetransaction, the user's shipping address, and/or the user's billingaddress. In a further example, the server computer 140 may alsodetermine a name associated with the merchant, a name of a parentorganization associated with the merchant, a physical address associatedwith the merchant, prior history associated with the merchant, and frauddata associated with transactions in which the merchant was involved.The information or attributes associated with the merchant may beobtained from the resource provider information database 142 within theserver computer 140. Other information regarding the attributes of thetransaction may be obtained from a variety of the sources ofinformation, including the resource provider computer 130 which maystore records of the specific items purchased by the user at theparticular resource provider, the authorizing entity computer 110, whichmay have data regarding the time of authorization as well as the user'sprior transaction history, and a processing network (see 550 in FIG. 5).

The processing network may be a “switch” that resides between aplurality of acquirers (and their merchants) and issuers, and may routeand log transactions occurring between these entities. It may, forexample, transport and log decline and chargeback messages, and thisinformation may be used to drive the online resolution interview scriptas explained below. For instance, in some embodiments, the processingnetwork may see that a particular merchant X has had a disproportionatenumber of chargebacks in the past 24 hours relative to other merchantsin the same merchant category. Thus, in the initial dispute requestprovided by the user to the authorizing entity computer 110 and theserver computer 140, the user may only need to provide his or her creditor debit card account number. In some cases, even the credit or debitcard account number need not be provided, as the device identifier(e.g., a phone number) of the user computer 120 may be linked to theuser's debit or credit card number, and the server computer 110 mayautomatically determine the credit or debit card account used by theuser computer 120. The server computer 110 may recognize that it islikely that the user is calling about problems with merchant X. Theserver computer 110 may then prompt the user, without any informationother than the user's credit or debit card number, “Are you callingabout merchant X?”.

Other information that may drive the interview script with the user mayinclude information from the global resolution database 146. Thisdatabase may include data regarding disputes with other users. Thedispute data in the global resolution database 146 may containinformation on disputes between a large number of merchants and users(and their issuers). Unlike the data that may reside in the processingnetwork described above, the data in the global resolution database 146may contain more detailed information regarding disputes (e.g., at leastthe name of the user, the name of the merchant, the amount of thedispute, the resolution of the dispute, the acquirer, and the issuer).The data in the processing network, however, may contain more up to dateand real time transaction information as a large number of disputes maynot yet have been initiated, but the data from other transactionsprocessed by the processing network may be used to predict the nature ofthe dispute that the user is currently involved in.

Similar to the above example, if the global resolution database 146 hasseen a rise in the number of disputes about merchant X for a particularproduct Y over the last week, this information may be used to drive aninterview script with the current user. For example, the server computer110 may then prompt the user, without any information other than theuser's credit or debit card number, “Are you calling about product Yoffered for sale by merchant X?” In this scenario, the user need notfill out a form, or even type in or articulate the name of the productor merchant involved in the dispute, but only needs to reply “yes” or“no.” Compared to conventional systems, this can provide for much fasterprocessing and can result in less human error (e.g., as may result fromthe user typing in or providing incorrect information).

At step s5, after the server computer 140 performs real-time researchpertaining to the disputed transaction, the server computer 140 mayaccess a ruleset database 144 in order to determine further actions totake. The ruleset database 144 may contain rules that can be used fordetermining a set of questions or interactions to ask to the userinitiating the dispute, define responses, define processes, and definepossible results to the interactions with the user. The ruleset database144 may contain different sets of rules (merchant customizable ruleset)depending on the merchant for which the dispute is initiated against.For example, a merchant that is an airline may have a different set ofprompts than a merchant that is an electronics store. The rulesetdatabase 144 may also contain different sets of rules (issuercustomizable ruleset) depending on the authorizing entity involved withthe disputed transaction.

The following examples may help illustrate a set of questions orinteractions that can be asked the user within different use cases. Ifthe user initiates a dispute regarding cancelled/returned merchandiseand the merchant is an online ticket retailer, the ruleset database 144may include a rule that concludes that the ticket is for an event andthe user may be advised about the available cancellation policy and theliability per the terms and conditions of the merchant. If the userinitiates a dispute regarding cancelled/returned merchandise and themerchant is an Internet Service Provider (ISP), the user may be asked toapprove an automatic blocking of all future recurring transactions fromthat merchant as part of the dispute resolution process. If the user isinitiating a dispute for a fraudulent transaction, the ruleset database144 may include a rule(s) that if the card was used at any compromisedmerchant location during a certain time window, to flag the user's cardas potentially compromised. Additional questions may be presented to theuser to approve the automatic blocking of the card, confirmation toreissue a new card, and the user's preferred shipping method to receivethe new card.

At step s6, after the server computer 140 accesses a ruleset database144 in order to determine further actions to take, the server computer140 may invoke an online session with the user computer 120. The onlinesession may be used by the server computer 140 to obtain moreinformation and facts related to the disputed transaction from the userof the user computer 120. The information and facts gathered by theserver computer 140 from the user may be information and facts thattypically would require a live agent or caseworker associated with theauthorizing entity computer 110 to gather. The information and factsrelated to the dispute may be obtained by the server computer 140 andfrom the user by causing a series of questions to be presented to theuser via the user computer 120. The series of questions may be dynamicin nature, in the sense that the questions to be presented may depend onthe user's response to previously asked questions. The online sessionmay be initiated by the server computer 140 with the user computer 120via the authorizing entity computer 110. For example, the online sessionmay be initiated via an issuer application associated with theauthorizing entity computer 110 that is being executed on the usercomputer 120.

At step s7, after the server computer 140 invokes an online session withthe user computer 120 (e.g., either directly or through the authorizingentity computer 110), the server computer 140 may cause a first questionto be presented to the user, via the user computer 120. The firstquestion presented may be based on the accessed ruleset database 144 instep s5. For example, the first question presented may ask the userwhich good or service he/she would like to dispute, if more than onegood or service was involved in the disputed transaction. In anotherexample, the first question may ask about the user's history with themerchant by asking the user how many times in the past six months theuser has conducted transactions with the merchant.

At step s8, after the server computer 140 causes the first question tobe presented to the user via the user computer 120, the user may input aresponse to the question via the user computer 120. The user may selectfrom a list of responses or may manually enter a response to thepresented first question. The user's response may then be relayed backto the server computer 140, via the authorizing entity computer 110, bythe user computer 120. At step s9, the server computer 140 may registerand log the user's response to the first question presented to the user.

At this point, step s7 may repeat such that the server computer 140 maycause a second question to be presented to the user, via the usercomputer 120. The second question presented may also be based on theaccessed ruleset database 144 in step s5 in addition to the response tothe first question that was registered and logged in step s9. In otherwords, the response to the first question presented to the user mayinfluence the second question that is presented to the user. Forexample, if the first question asked the user which good or servicehe/she would like to dispute, and the user responded that the good was atelevision set, the second question may ask the user what may be wrongwith the television set and provide the following options as responsesto the second question: (1) Does not turn on; (2) No volume; (3)Physical Damage; (4) Other. In this way, the online resolution analysisserver computer (e.g., server computer 140) may intelligently gather theappropriate information and facts from the user of the user computer 120that would typically require a caseworker or live agent to gather. Theintelligent gathering of the appropriate information and facts mayprovide numerous advantageous including an improved user experience,efficiency, and cost savings for the authorizing entity computer 110.

This process may repeat for each subsequent question presented to theuser until the server computer 140 determines that it has gatheredenough facts or information pertaining to the dispute in order to takean action on the dispute or present the gathered information for furtheranalysis by a caseworker or live agent. Referring back to step s9, afterresponses for all the presented questions are received, the responsesmay be stored in a data storage element which may later be accessed by athird-party. In some embodiments, the third-party may be the same as theauthorizing entity computer 110, or may be an independent disputeresolution party that may make a decision to resolve the dispute.

Further details of the server computer 140 are described in thefollowing description.

FIG. 2 shows a flowchart 200 illustrating a process for online disputeanalysis. At step 202, information identifying a transaction between auser computer 120 and a resource provider computer 130 may be receivedby the server computer 140. This information may be received in responseto a user of the user computer 120 initiating a dispute against amerchant associated with the resource provider computer 130. Forexample, the user may have purchased goods from the merchant that theuser has found unsatisfactory and for which a the user and the merchantcould not come to a resolution on their own. The information identifyingthe transaction may include information identifying that the user hasinitiated the disputed. This information may include a user deviceidentifier (e.g., a phone number, serial number, secure element ID,etc.), a primary account number (e.g., a credit or debit card accountnumber), or any other user ID. Other information might include theproducts purchased, or the merchant at which the user has transacted.However, the information identifying the transaction is preferablyminimized to improve the speed of processing. Transaction informationcan also be identified from the purchase statement, for example if thecardholder decides to initiate dispute from the monthly statement. Insome cases, the information may or may not directly relate to the actualtransaction. For example, only a phone number may be provided by theuser and the system can determine the remainder of the information fromdata collected by the system, and prompts to the user. In someembodiments, the user may have initiated the dispute via an issuerapplication associated with an authorizing entity computer 110 andexecuting on the user computer 120.

At step 204, one or more attributes associated with the identifiedtransaction and one or more attributes associated with the resourceprovider computer 130 may be accessed by the server computer 140 fromthe resource provider information database 142. The one or moreattributes associated with the identified transaction may include, butis not limited to, a transaction amount, transaction date, transactiontime, transaction type, item name, website address, shipping address, orbilling address. The one or more attributes associated with the resourceprovider computer may include, but is not limited to, of a resourceprovider computer name, parent organization name, resource providercomputer address, resource provider computer history, or fraud data. Theserver computer may also access a ruleset database 144 in order todetermine further actions to take. The ruleset database 144 may containrules that can be used for determining a set of questions orinteractions to ask to the user initiating the dispute, defineresponses, define processes, and define possible results to theinteractions with the user. The ruleset database 144 may containdifferent sets of rules depending on the merchant for which the disputeis initiated against. The global resolution database 146 may containdata regarding past disputes by other users (and their issuers) and/ormerchants (and their acquirers).

At step 206, the server computer 140 may cause the presentation of afirst question pertaining to the transaction based at least in part onthe accessed one or more attributes associated with the identifiedtransaction and the accessed one or more attributes associated with theresource provider computer 130. The first question may be presented tothe user via the user computer 120 and for the purposes of aiding inobtaining the information necessary to resolve the dispute. For example,an issuer application executing on the user computer 120 may present thefirst question to the user via a user interface (UI) of the issuerapplication. The first question presented may be based on the accessedruleset database 144 in step 204. For example, the first questionpresented may ask the user which good or service he/she would like todispute, if more than one good or service was involved in the disputedtransaction. In another example, the first question may ask about theuser's history with the merchant by asking the user how many times inthe past six months the user has conducted transactions with themerchant. In some embodiments, the first question to be presented to theuser may be generated by a machine learning model, where the machinelearning model may take as inputs the rules in the ruleset database, oneor more attributes associated with the identified transaction, or one ormore attributes associated with the resource provider computer 130.

At step 208, the server computer 140 may receive, from the user computer120, a response to the first question that was presented to the user instep 206. The user's response may have been selected from a list ofresponses or may have been manually entered by the user. As describedfurther below, the user's response to the first question may influencethe next question, if any, to be presented to the user.

At step 210, the server computer 140 may determine whether anyadditional questions need to be presented to the user in order to aid inobtaining the information necessary to resolve the dispute or prepareinformation for a third-party to resolve the dispute. If the servercomputer 140 determines that no further questions are needed to bepresented to the user, the method may continue to step 216. Otherwise,if the server computer 140 determines that additional questions need tobe presented to the user, the method may continue to step 212.

At step 212, if the server computer 140 determined that additionalquestions need to be presented to the user, the server computer 140 maypresent another question pertaining to the transaction based at least inpart on responses to previous questions. In other words, the response tothe first question presented to the user may influence the secondquestion that is presented to the user. In this manner, the servercomputer 140 may intelligently gather the appropriate information andfacts from the user of the user computer 120 that would typicallyrequire a caseworker or live agent to gather. In some embodiments, eachquestion subsequent to the first question may also be generated by themachine learning model described above. The series of questionspresented to the user may be used for gathering information on theuser's side of the story pertaining to the dispute. The automated andintelligent question asking process may reduce the amount of resourcesrequired by the authorizing entity computer 110 and avoid costly callsto call centers. Responses to the questions may be used to referencetrends identified through historical transaction analysis and merchantperformance, incorporating risk models, and learning from interactionsproviding intelligent and predictive responses throughout thequestionnaire exchange.

At step 214, the user may provide a response to a question presented tothe user subsequent to the first question presented to the user. Theresponse to the question may be recorded and the process may then returnagain to step 210 where the server computer 140 may again determinewhether any additional questions need to be presented to the user inorder to aid in obtaining the information necessary to resolve thedispute or prepare information for a third-party to resolve the dispute.If the server computer 140 determines that no further questions areneeded to be presented to the user, the method may continue to step 216.Otherwise, if the server computer 140 determines that additionalquestions need to be presented to the user, the method may continue tostep 212. This process may repeat and further subsequent questions maybe presented to the user until the process continues to step 216.

At step 216, the server computer 140 may store the received responsesfor all of the presented questions in a data storage element. The datastorage element may later be accessed by a third-party. In someembodiments, the third-party may be the same as the authorizing entitycomputer 110, or may be an independent dispute resolution party that maymake a decision to resolve the dispute. The data storage element may beaccessible via the online resolution analysis system, for example, byaccessing an application programming interface (API). The third-partymay be authorized to enforce a payment refund from the resource providercomputer 130 to the authorizing entity computer 110 based at least inpart on data stored in the data storage element. In some embodiments,the user may be presented with different options for resolving thedispute. The options may be based on the responses to the questions, theaccessed one or more attributes associated with the identifiedtransaction, the accessed one or more attributes associated with thesecond party, or the accessed ruleset. For example, the one or moreoptions may include a full refund for the disputed transaction, areplacement good for a defective purchased good, a store credit, etc.

FIG. 3 shows a server computer 140, according to some embodiments. Thecomponents of server computer 140 may be used to implement an onlineresolution analysis server computer. The server computer 140 includes aninput/output interface 310, a memory 320, a processor 330, a resourceprovider information database 142, a ruleset database 144, a globalresolution database 146, and a non-transitory computer-readable medium340. In some embodiments, server computer 140 may reside within apayment processing network cloud or may also operate as a subsystem ofthe authorizing entity computer 110.

The input/output (I/O) interface 310 is configured to receive andtransmit data from external devices or apparatuses. For example, the I/Ointerface 310 may receive a dispute initiation request from a usercomputer 120. The I/O interface 310 may also be used for directinteraction with the server computer 140. The server computer 140 mayaccept input from an input device such as, but not limited to, akeyboard, keypad, or mouse. Further, the I/O interface 140 may displayoutput on a display device.

Memory 320 may be any magnetic, electronic, or optical memory. It can beappreciated that memory 320 may include any number of memory modules. Anexample of memory 320 may be dynamic random access memory (DRAM).

Processor 330 may be any general-purpose processor operable to carry outinstructions on the server computer 140. The processor 330 is coupled toother units of the server computer 140 including input/output interface310, memory 320, and computer-readable medium 340.

Computer-readable medium 340 may be any magnetic, electronic, optical,or other computer memory device. In some embodiments, the computerreadable medium 340 may comprise code, executable by the processor 330for implementing a method comprising: receiving, from a user computerthat is a party to a transaction and at a server computer, informationidentifying a transaction between the user computer and a resourceprovider computer; accessing, by the server computer and from adatabase, one or more attributes associated with the identifiedtransaction and one or more attributes associated with the resourceprovider computer; presenting, by the server computer, a first questionpertaining to the transaction based at least in part on the accessed oneor more attributes associated with the identified transaction and theaccessed one or more attributes associated with the resource providercomputer; receiving, from the user computer and by the server computer,a response to the first question; presenting, by the server computer, asecond question pertaining to the transaction based at least in part onthe received response to the first question; receiving, from the usercomputer and by the server computer, a response to the second question;and storing, by the server computer, the received first response and thereceived second response in a data storage element, wherein the datastorage element is accessible by an authorizing entity computer.

The computer-readable medium 340 may also include a questionpresentation module 340A, a data storage element generation module 340B,a machine learning module 340C, and an online dispute resolution API340D.

The question presentation module 340A may comprise code that, whenexecuted by processor 330, can cause the presentation of one or morequestions to be displayed to a user via the user computer 120. Thequestion presentation module 340A may transmit data to the user computer120, either directly or via the authorizing entity computer 110,pertaining to the question(s) to be presented. The question presentationmodule may either directly generate the question(s) to be presentedaccording to the attributes and rulesets described above, or mayinterface with the machine learning module 340C to obtain question(s)generated by the machine learning module. The question presentationmodule 340A may also facilitate the receipt of responses to thequestions provided by the user via the user computer 120.

The data storage element generation module 340B may comprise code that,when executed by processor 330, generates a data storage elementcomprising the responses to the questions presented to the user, theresponses provided by the user via the user computer 120. The generateddata storage element may also include additional information pertainingto the transaction that was gathered by the server computer 140 (e.g.,data accessed from the resource provider information database 142, theruleset database 144, and/or the global resolution database 146). Insome embodiments, the data storage element may be encrypted. The datastorage element may be accessible by a third-party dispute resolutionentity via the online dispute resolution API 340D.

The machine learning module 340C comprise code that, when executed byprocessor 330, that can learn from and make predictions on data. Forexample, the machine learning module 340C may generate a question forpresentation to the user based on the accessed one or more attributesassociated with the identified transaction and the accessed one or moreattributes associated with the resource provider computer 130.Additionally, the generated questions may also be based on the user'sprior responses to previously presented questions. All of this data maybe input to the machine learning module 340C and the machine learningmodel may then generate a question along with possible responses to thequestions. The generated questions and response options may betransmitted to the question presentation module 340A, to facilitatepresentation to the user of the user computer 120. The machine learningmodule 340C may use suitable machine learning models based on algorithmsincluding, but not limited to: neural networks, decision trees, supportvector methods, and K-means algorithms.

The online dispute resolution API 340D may comprise code that, whenexecuted by processor 330, provides an accessible interface forthird-party dispute resolution entities to access the data storageelement generated by the data storage element generation module 340B. Inone example, the online dispute resolution API 340D may provide forwebpage access of the data storage element.

FIG. 4A shows a screenshot of a user interaction with the online disputeresolution system via a user interface 410 of an application executingon the user computer 120, according to some embodiments. The user mayinitiate a dispute with the online dispute resolution system byselecting an option to “chat” with a dispute resolution robot. Thedispute resolution robot may serve as the front-end for interaction withthe user and may function as a result of the components described withrespect to the server computer 140. Upon chatting with the disputeresolution robot, the user may express his/her desire to initiate adispute by typing and sending the text “Dispute” to the robot. The robotmay reply by asking the user which transaction the user would like todispute. The robot may present a few response options outlining recenttransactions the user has completed based on information gathered by theserver computer 140 in accordance with the description above. In thisexample, the user's recent transactions include (1) a purchase for anOculus Rift at the merchant Amazon for a transaction amount of $599 and(2) a purchase for AirPods at the merchant Apple for a transactionamount of $159. The user may respond by sending the text “AirPods,”indicating that the user wishes to dispute the transaction involving theAirPods. The robot may then ask the user what the reason for the disputeis and present response options corresponding to typical reasons for adispute. This question may be intelligent in the sense that servercomputer 140 may have knowledge that AirPods are an electronic item andelectronic items are often disputed for being defective, an thus maypresent “defective” as one of the response options. The user mayindicate that the AirPods are in fact defective by sending the text“Defective” to the robot. If the server computer 140 determines that nofurther questions need to be presented to the user prior to generatingthe data element for access by a third-party dispute resolution entity,the robot may respond by saying “Thank you! We will investigate furtherand contact you soon.” The data storage element may then be created withthe user's responses and any further information or facts gathered bythe server computer 140 in accordance with the description above.

In some embodiments, upon an initial interaction with the disputeresolution robot, the user may first be presented with a list of recenttransactions completed by the user. The user may then select to disputeone of the transactions by selecting a “Dispute” button presented nextto the recent transactions that the user wishes to dispute. This may bebegin the dispute process with the online dispute resolution robot. Insome embodiments, the user may login to a website associated with theauthorizing entity computer 110 or server computer 140 and select a“dispute” button next to a list of recent transactions presented to theuser to begin the dispute process. In some embodiments, the user mayreceive transaction alerts at the user computer 120 as transactions arecompleted, and the user may select to dispute the transaction inresponse to the transaction alert. These are all examples of the processmay be initiated to dispute a transaction.

FIG. 4B shows another screenshot of a user interaction with the onlinedispute resolution system via a user interface 410 of an applicationexecuting on the user computer 120, according to some embodiments.Similar to FIG. 4A, in this example, the user has also initiated adispute with the online dispute resolution system. This time, the userhas indicated that he wishes to dispute the transaction for a PanasonicTV at the merchant Grey Market Televisions for a transaction amount of$899. The server computer 140 may have gathered information or factspertaining to Grey Market Televisions and may be aware that thismerchant has had a large amount of disputes filed against them and thusmay be a fraudulent merchant. Accordingly, the robot may thenproactively ask the user if the transaction was a fraudulenttransaction. This illustrates the intelligence of the presentation ofthe questions and how the subsequent questions are based on the user'sresponses to prior questions as well as information and facts gatheredby the server computer 150 pertaining to the transaction and themerchant involved. The user may then respond that the transaction wasfraudulent by typing and sending “Yes.” The robot may then ask the userwhether the user's card was lost or stolen since the user had indicatedthat this was a fraudulent transaction. The user may reply “No”indicating that the card is still in the user's possession. In thisexample, the server computer 150 may be able to provide a resolution tothe dispute without the involvement of a third-party dispute resolutionentity or without further interaction by a caseworker or agent of theauthorizing entity computer 110. For example, the server computer 150may be able provide the user with an immediate refund of the transactionamount because of the user's response that the transaction wasfraudulent combined with the past history of the merchant being known asa fraudulent merchant.

FIG. 5 shows a block diagram of a transaction processing system that canuse a portable device with access data. FIG. 5 shows a user 506 that canoperate a portable device 510. The user 506 may use the portable device510 to pay for a good or service at a resource provider such as amerchant. The resource provider may operate a resource provider computer530 and/or an access device 520. The resource provider may communicatewith an authorization computer 560 (e.g., an issuer computer) via atransport computer 540 (e.g., an acquirer computer) and a processingnetwork 550 (e.g., a payment processing network).

The processing network 550 may include data processing subsystems,networks, and operations used to support and deliver authorizationservices, exception file services, and clearing and settlement services.An exemplary payment processing network may include VisaNet™. Paymentprocessing networks such as VisaNet™ are able to process credit cardtransactions, debit card transactions, and other types of commercialtransactions. VisaNet™, in particular, includes a VIP system (VisaIntegrated Payments system) which processes authorization requests and aBase II system which performs clearing and settlement services. Thepayment processing network may use any suitable wired or wirelessnetwork, including the Internet.

A typical payment transaction flow using a portable device 510 at anaccess device 520 (e.g. POS location) can be described as follows. Auser 506 presents his or her portable device 510 to an access device 520to pay for an item or service. The portable device 510 and the accessdevice 520 interact such that access data from the portable device 510(e.g. PAN, a payment token, verification value(s), expiration date,etc.) is received by the access device 520 (e.g. via contact orcontactless interface). The resource provider computer 530 may thenreceive this information from the access device 520 via an externalcommunication interface. The resource provider computer 530 may thengenerate an authorization request message that includes the informationreceived from the access device 520 (i.e. information corresponding tothe portable device 510) along with additional transaction information(e.g. a transaction amount, merchant specific information, etc.) andelectronically transmits this information to a transport computer 540.The transport computer 540 may then receive, process, and forward theauthorization request message to a processing network 550 forauthorization.

In general, prior to the occurrence of a credit or debit-cardtransaction, the processing network 550 has an established protocol witheach authorization computer on how the issuer's transactions are to beauthorized. In some cases, such as when the transaction amount is belowa threshold value, the processing network 550 may be configured toauthorize the transaction based on information that it has about theuser's account without generating and transmitting an authorizationrequest message to the authorization computer 560. In other cases, suchas when the transaction amount is above a threshold value, theprocessing network 550 may receive the authorization request message,determine the issuer associated with the portable device 510, andforward the authorization request message for the transaction to theauthorization computer 560 for verification and authorization. Once thetransaction is authorized, the authorization computer 560 may generatean authorization response message (that may include an authorizationcode indicating the transaction is approved or declined) and transmitthis electronic message via its external communication interface toprocessing network 550. The processing network 550 may then forward theauthorization response message to the transport computer 540, which inturn may then transmit the electronic message to comprising theauthorization indication to the resource provider computer 530, and thento the access device 520.

At the end of the day or at some other suitable time interval, aclearing and settlement process between the resource provider computer530, the transport computer 540, the processing network 550, and theauthorization computer 560 may be performed on the transaction.

It should be understood that the present invention as described abovecan be implemented in the form of control logic using computer softwarein a modular or integrated manner. Based on the disclosure and teachingsprovided herein, a person of ordinary skill in the art will know andappreciate other ways and/or methods to implement the present inventionusing hardware and a combination of hardware and software. Any of theabove mentioned entities may operate a computer that is programmed toperform the functions described herein.

Any of the software components, processes or functions described in thisapplication may be implemented as software code to be executed by aprocessor using any suitable computer language such as, for example,Java, C++ or Perl using, for example, conventional or object-orientedtechniques. The software code may be stored as a series of instructions,or commands on a computer readable medium, such as a random accessmemory (RAM), a read only memory (ROM), a magnetic medium such as ahard-drive or a floppy disk, or an optical medium such as a CD-ROM. Anysuch computer readable medium may reside on or within a singlecomputational apparatus, and may be present on or within differentcomputational apparatuses within a system or network.

Different arrangements of the components depicted in the drawings ordescribed above, as well as components and steps not shown or describedare possible. Similarly, some features and sub-combinations are usefuland may be employed without reference to other features andsub-combinations. Embodiments of the invention have been described forillustrative and not restrictive purposes, and alternative embodimentswill become apparent to readers of this patent. Accordingly, the presentinvention is not limited to the embodiments described above or depictedin the drawings, and various embodiments and modifications can be madewithout departing from the scope of the claims below.

What is claimed is:
 1. A method for automated analysis using machinelearning, comprising: receiving, from a user computer that is a party toa transaction and at a server computer, information that can be used toidentify a transaction between the user computer and a resource providercomputer; determining, by the server computer and from a database, oneor more attributes associated with the transaction and one or moreattributes associated with the resource provider computer; presenting,by the server computer, a first question pertaining to the transactionbased at least in part on the accessed one or more attributes associatedwith the identified transaction and the accessed one or more attributesassociated with the resource provider computer; receiving, from the usercomputer and by the server computer, a response to the first question;presenting, by the server computer, a second question pertaining to thetransaction based at least in part on the received response to the firstquestion; receiving, from the user computer and by the server computer,a response to the second question; and storing, by the server computer,the received first response and the received second response in a datastorage element, wherein the data storage element is accessible by anauthorizing entity computer.
 2. The method of claim 1, wherein the datastorage element is accessible by the authorizing entity computer via anonline resolution analysis system.
 3. The method of claim 1, wherein theinformation that can be used to identify the transaction between theuser computer and a resource provider computer is received via anapplication associated with the resource provider computer executing onthe user computer.
 4. The method of claim 1, wherein the one or moreattributes associated with the transaction and the one or moreattributes associated with the resource provider computer are determinedautomatically by the server computer by receiving only an identifierassociated with the user computer.
 5. The method of claim 1, wherein thefirst question and the second question are part of an interview scriptthat is automatically created using a machine learning algorithm, themachine learning algorithm including a neural network or a K-meansalgorithm.
 6. The method of claim 1, wherein the first question and thesecond question are part of an interview script that is automaticallycreated using data from a processing network that operates as a switch.7. The method of claim 1, further comprising providing, by the servercomputer and to the user computer, one or more options for answering thefirst and second questions.
 8. The method of claim 7, wherein the one ormore options are based at least in part on the response to the firstquestion, the response to the second question, the accessed one or moreattributes associated with the identified transaction, or the accessedone or more attributes associated with the resource provider computer.9. The method of claim 7, wherein the one or more options are based atleast in part on a ruleset applied to the dispute, wherein the rulesetis based at least in part on the accessed one or more attributesassociated with the resource provider computer.
 10. The method of claim1, wherein the first question and the second question are generated by amachine learning model.
 11. A server computer, comprising: a processor;and a non-transitory computer readable medium, the non-transitorycomputer readable medium comprising computer executable code forexecuting a method for resolving a dispute, the method comprising:receiving, from a user computer that is a party to a transaction,information that can be used to identify a transaction between the usercomputer and a resource provider computer; determining, from a database,one or more attributes associated with the transaction and one or moreattributes associated with the resource provider computer; presenting afirst question pertaining to the transaction based at least in part onthe accessed one or more attributes associated with the identifiedtransaction and the accessed one or more attributes associated with theresource provider computer; receiving, from the user computer, aresponse to the first question; presenting a second question pertainingto the transaction based at least in part on the received response tothe first question; receiving, from the user computer, a response to thesecond question; and storing the received first response and thereceived second response in a data storage element, wherein the datastorage element is accessible by an authorizing entity computer.
 12. Theserver computer of claim 11, wherein the data storage element isaccessible by the authorizing entity computer via an online resolutionanalysis system.
 13. The server computer of claim 11, wherein theinformation that can be used to identify the transaction between theuser computer and a resource provider computer is received via anapplication associated with the resource provider computer executing onthe user computer.
 14. The server computer of claim 11, wherein the oneor more attributes associated with the transaction and the one or moreattributes associated with the resource provider computer are determinedautomatically by the server computer by receiving only an identifierassociated with the user computer.
 15. The server computer of claim 11,wherein the first question and the second question are part of aninterview script that is automatically created using a machine learningalgorithm, the machine learning algorithm including a neural network ora K-means algorithm.
 16. The server computer of claim 11, wherein thefirst question and the second question are part of an interview scriptthat is automatically created using data from a processing network thatoperates as a switch.
 17. The server computer of claim 11, wherein themethod further comprises providing, by the server computer and to theuser computer, one or more options for answering the first and secondquestions.
 18. The server computer of claim 17, wherein the one or moreoptions are based at least in part on the response to the firstquestion, the response to the second question, the accessed one or moreattributes associated with the identified transaction, or the accessedone or more attributes associated with the resource provider computer.19. The server computer of claim 17, wherein the one or more options arebased at least in part on a ruleset applied to the dispute, wherein theruleset is based at least in part on the accessed one or more attributesassociated with the resource provider computer.
 20. The server computerof claim 11, wherein the first question and the second question aregenerated by a machine learning model.